A new image-based method for event detection and extraction of noisy hydrophone data

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Abstract

In this paper, a new image based method for detecting and extracting events in noisy hydrophone data sequence is developed. The method relies on dominant orientation and its robust reconstruction based on mutual information (MI) measure. This new reconstructed dominant orientation map of the spectrogram image can provide key segments corresponding to various acoustic events and is robust to noise. The proposed method is useful for long-term monitoring and a proper interpretation for a wide variety of marine mammals and human related activities using hydrophone data. The experimental results demonstrate that this image based approach can efficiently detect and extract unusual events, such as whale calls from the highly noisy hydrophone recordings. © 2011 Springer-Verlag.

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Sattar, F., Driessen, P. F., & Tzanetakis, G. (2011). A new image-based method for event detection and extraction of noisy hydrophone data. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6754 LNCS, pp. 328–337). https://doi.org/10.1007/978-3-642-21596-4_33

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